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Sponsored by
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akashmaggon / QWEN_SFT_Reasoning_final
Model's Last Updated: October 01 2025
Introduction of QWEN_SFT_Reasoning_final
Model Details of QWEN_SFT_Reasoning_final
Model Card for QWEN_SFT_Reasoning_final
This model is a fine-tuned version of Qwen/Qwen3-14B . It has been trained using TRL .
Quick start
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="akashmaggon/QWEN_SFT_Reasoning_final", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 0.23.0
- Transformers: 4.56.1
- Pytorch: 2.8.0+cu126
- Datasets: 4.0.0
- Tokenizers: 0.22.0
Citations
Cite TRL as:
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}
Runs of akashmaggon QWEN_SFT_Reasoning_final on huggingface.co
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More Information About QWEN_SFT_Reasoning_final huggingface.co Model
Url of QWEN_SFT_Reasoning_final
QWEN_SFT_Reasoning_final huggingface.co Url
Provider of QWEN_SFT_Reasoning_final huggingface.co
Other API from akashmaggon
Updated:January 22 2025
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